Data analytics solutions used to support business decisions is not a new phenomenon.
This is a facet that has been around for a number of years in the field of commerce as the leading corporations have found a means of accessing information at the top level.
Yet this approach is now widespread amongst the business community, using data to determine how campaigns and maneuvers will be made without relying on pure old fashioned instinct.
Here we will discuss how this practice helps to support business intelligence whilst noting how it can falter.
One way in which data analytics solutions work to support the decision making process is through its diagnostic features that discerns how patterns and behaviours are established. From seasonal alterations that affect how consumers interact with the brand to their online preferences, there is in-depth detail that this field focuses on that makes it a valuable asset for any organisation in the world of commerce.
Reports on Historical Performance
A tangible form where data analytics solutions help to support the key decision making process is in relation to the reporting facet of the operation. By giving a detailed briefing over the positives and negatives of various campaigns and initiatives run by the organisation, managers have real time data to examine where opportunities were seized and lost all before they endeavour on a fresh project. Some professionals in leadership positions are less concerned about the need to revisit old reports, but those who want to learn from history will heed the advice derived from these specified reports.
Making Insightful Predictions
Forecasting insights is something that can really help a business when it comes to data analytics offering support for a company. Also known as predictive analytics, this is a practice that sees statistics and algorithms combine to highlight and identify trends before making an educated guess on future patterns and movements.
There can never be guarantees or 100% success rates with these programs, but they are utilised to give a statistical rundown of what is likely to occur given the available information. When informing the decision making process, it is paramount that managers and executives understand the odds and the risks involved with their moves, a scenario that is boosted by the introduction of data analytics.
Catering Business To “Big Data”
Should a company be large enough to involve a term known as “big data” where metrics and statistical analysis ventures into the real of requiring a warehouse to store the information, then the pressure to house that data becomes paramount. This is where data analytics will only be able to support the decision making phase if there is a sound framework in place to cater to the 4V data dilemma – volume, velocity, variety and veracity. Loading and extracting information on old data storage models that are no catered to 2018 demands such as the cloud are inadequate, opening up human error and poor decision making processes.
Data-Driven Culture First
What must be established when it comes to data analytics solutions working to support the decision making process is that there is a culture within the organisation that respects and enacts this approach at all levels. This idea becomes a failing practice when individuals in key positions and staffers across the board fail to trust the need to base their decisions on the data accumulated through these endeavours.
By having an infrastructure that embraces this working model, companies can transition their approach to be a reactive brand that responds to threats and lost opportunities to a proactive brand that ventures forward with precision and ambition in equal measure.
Data analytics solutions clearly can support managers and key stakeholders make decisions that are based on accurate and real time information. The good news in 2018 is that a comprehensive business intelligence apparatus is not just open to the select few at the top of the pyramid, as the evolution of technology and the freedom of access has made that a right of every enterprise.
However, it must be noted that a solid structure must be established where the participants at all levels have bought into the need to focus on data first. Without that support network, the other benefits become obsolete.